Читать книгу Standing on the Sun - Christopher Meyer - Страница 24

Having reviewed the essential concepts of environment, coevolution, breeding, fitness, and selection, we should now turn our focus to feedback. The effect of what happened yesterday on what will happen tomorrow is a powerful force in any ecology, biological or economic. Performance reviews don't only describe what happened in the past; they affect how individuals will behave in the future. Market acceptance is a form of feedback that determines what will get made.

The powerful operation of feedback has not been, in the past, a force recognized in economists' models.¹¹ The academic scribblings of most of the twentieth century have assumed that systems remain static and have focused on creating the methods for optimizing within them.

We are in a moment now, however, when the underlying ideas of economics are in flux, and the focus has moved to understanding changes in dynamic systems. It's been a gradual encroachment of ideas, to recall Keynes's language, but it has already managed to influence the thinking of practical managers. One fundamental work was Brian Arthur's Increasing Returns and Path Dependence in the Economy. Arthur described a particular positive feedback loop and the dynamics of increasing returns in network businesses, and the phenomenon of lock-in became self-evident to technology executives, if controversial among economists (a classic case of an idea working fine in practice but not in theory). The idea of first-mover advantage, not an unknown thought in business of the 1980s but rarely relevant (and often subordinated to the fast follower strategy), grew in importance.

No doubt it is true that static analysis wasn't always as inadequate as it is today; the world changes faster now. Inventor Ray Kurzweil maintains that the rate of technological change doubles every decade. But the criticism of it has deeper, older roots than you might imagine. As early as the 1890s, Thorstein Veblen used the term evolutionary economics. He introduced it in an 1898 article called “Why Is Economics Not an Evolutionary Science?” that combines the mid-nineteenth-century thinking of Marx with that of Darwin. Its first line: “M. G. de Lapouge recently said, ‘Anthropology is destined to revolutionise the political and the social sciences as radically as bacteriology has revolutionised the science of medicine.’ Insofar as he speaks of economics, the eminent anthropologist is not alone in his conviction that the science stands in need of rehabilitation.”

We leave most of the history of these ideas for a different kind of book—namely, Eric Beinhocker's Origin of Wealth, which gives a full account. Briefly, though, as the twentieth century wore on, economics was influenced far less by evolutionary science than by engineering. It became a discipline focused on questions of optimizing prices, processes, and resource allocation in a world assumed to be in stable equilibrium. If you've studied economics—and probably even if you haven't—you've been introduced to a picture of a supply curve and a demand curve meeting at a market-clearing point defined by a price and a quantity. You might have spent the next semester studying what happened when you perturbed this equilibrium—say, by raising or lowering price. Your exam probably asked you to calculate the new equilibrium, given something called the price elasticity of demand.¹²

As Beinhocker writes, “The notion that the economy has a balancing point to which it naturally progresses is a theme that stretches back well before Smith … and remains a core concept of Traditional Economics today.” Analysis comparing such stable situations, called comparative statics, certainly can be useful—to estimate, for example, whether your current price is the profit-maximizing one, assuming that the costs of suppliers, the prices of competitors, and the availability of substitutes stay the same. Michael Porter's Five Forces model deals with this kind of thinking. Many managers, however, embraced that model as a kind of “Comparative Statics for Dummies,” enabling strategic thinking without the heavy lifting of equilibrium economics.

In the real world, when a business changes the pricing of its offering, for example, that action creates ripple effects. It puts other changes in motion—for example, in the prices offered by competitors and makers of complementary goods, in customers' expectations, and in the availability of inputs. Those reactions in turn create their own ripples. In real life, the water never returns to a glassy calm—the equivalent of that notional new equilibrium you calculated. Instead, the ripples and reactions continue forever. Sometimes, those changes create such disequilibrium that a market ceases to exist. Comparative statics would treat, say, digital modems as a substitute good for analog modems, but the field offers no help in understanding innovation and change—not to mention the ripple, or tsunami, of the digitization of the economy.

Robert Lucas at Carnegie Mellon deserves much of the credit for introducing another way of thinking. Around 1970, he began explorations in two new directions. First, he proposed that in principle, macroeconomics should be describable by building up a picture of the economy from the set of microeconomic decisions. That is to say, he posited that a picture of the whole should be able to emerge somehow from an understanding of the individual parts. At the time, economic methods afforded no way to incorporate this insight; you might describe individual choices, but there were no tools for aggregating them except to look at averages. Our GDP and other national statistics, developed during the Depression, could do no better. Today, though, cheap computing power has made it practical to simulate individual decisions and the effects of their interaction. You don't have to be a well-funded economist to run such simulations; this is how games such as SimCity work. The Sims are the agents, each Sim has a “personality” made up of a set of rules to live by, and the properties of the population (its overall happiness, for example) are the net results of all their choices and interactions. Such agent-based modeling (ABM)—understanding the macro-scale picture that emerges from the interactions of many individual decision makers—has become a foundation of adaptive systems research.¹³

Second, Lucas introduced recursive methods to macroeconomics, meaning that what happens next year is driven in part by what happened last year—in effect, acknowledging that last year's ripples cause this year's decisions. Ecologists use these methods to explain variation over time in the numbers of species in an ecology: last year's rain kept the hunters at home, so fewer grouse were shot; this year there are more grouse. The good hunting draws out hunters, so the year after that, fewer grouse, and the population exhibits a “business cycle” for no endogenous reason. Lucas won the 1995 Nobel Prize in Economics for his work and paved the way for others. Ideas that seemed far out in the early 1990s won Nobel Prizes in 2004 and NIH Pioneer Awards in 2009.

Economists call this way of thinking—assessing how one economic action creates a force that acts on others—dynamic analysis, in contrast to comparative statics. And, consistent with Lucas's first insight, it applies not only to a single market. According to Edward Prescott, who won the 2004 Nobel Prize in Economics, “The revolution in macroeconomics was to use dynamic economic reasoning.”¹⁴ Prescott carried Lucas's work on agents forward in the late 1970s, developing models of economic cycles incorporating these individual-driven dynamics.

In 1988, a landmark event took place: Kenneth Arrow and Philip Anderson, Nobel laureates in Economics and Physics, respectively, pulled together interested academics—including biologists and computer scientists—at the first of three conferences at the Santa Fe Institute (SFI) called “The Economy as an Evolving Complex System.” Reflecting on the relative states of the social sciences and physical sciences, one of the physicists in attendance compared economics to his recent observations of cars in Cuba, shut off from the modern world for forty years. “The mathematical Packards and DeSotos were the … techniques that the Marginalists had plundered from physics textbooks a hundred years ago.”¹⁵ The impatience for progress seems to be spreading; in 2010, George Soros pledged to spend $50 million over ten years to fund the Institute for New Economic Thinking.

The SFI conferences signaled an understanding that if economies were dynamic systems, there was some new thinking to do. At its core, SFI was devoted to the idea of generalizing from biological evolution to all systems that adapt. In this framework, any system made up of groups of interacting agents—decision makers, who might be birds in a flock, traders in a market, or individuals in a bar—behaves according to a set of rules, and these rules, properly applied, govern the evolution of all systems that adapt. What calculus did for physical sciences—allow lots of confusing data about falling cannon balls, magnetic fields, or chemical reactions to make sense by applying the same powerful toolkit to all of them—complexity scientists are trying to do for the social sciences. And because the biosphere is the adaptive system that has been studied most, some of this thinking involves observing how biological evolution works, abstracting those observations into mathematics, and then seeing whether the rules apply to other systems.¹⁶

It's not hard to see the parallel: the market is an environment in which certain goods and services thrive and, having been selected, shape a new generation of an industry's participants. And coevolution—the adjustments going on between the shape of finches' beaks and the forms of the flowers they feed on—is a fact of economic life: when Intel makes faster chips, Microsoft's code expands to fill them. Social scientists are at work modeling growth, innovation, economic coevolution, mergers and extinctions, and other economic phenomena to prove the parallels at deeper levels. A new economics that conforms to the facts of life—faster adaptation, variation of practices in contact with one another in a global economy—is on the way. But business needn't wait for the previous generation of economists to be defunct to take advantage of this perspective.